#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Common;
using HeuristicLab.Parameters;
using HeuristicLab.Data;
using HeuristicLab.Analysis;
namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
///
/// An operator for analyzing the solution diversity in a population.
///
[Item("SuccessfulOffspringAnalyzer", "An operator for analyzing certain properties in the successful offspring. The properties to be analyzed can be specified in the CollectedValues parameter.")]
[StorableClass]
public sealed class SuccessfulOffspringAnalyzer : SingleSuccessorOperator, IAnalyzer {
public ValueParameter SuccessfulOffspringFlag {
get { return (ValueParameter)Parameters["SuccessfulOffspringFlag"]; }
}
public ValueParameter> CollectedValues {
get { return (ValueParameter>)Parameters["CollectedValues"]; }
}
public ValueLookupParameter ResultsParameter {
get { return (ValueLookupParameter)Parameters["Results"]; }
}
public ILookupParameter GenerationsParameter {
get { return (LookupParameter)Parameters["Generations"]; }
}
public ValueParameter DepthParameter {
get { return (ValueParameter)Parameters["Depth"]; }
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SuccessfulOffspringAnalyzer(this, cloner);
}
[StorableConstructor]
private SuccessfulOffspringAnalyzer(bool deserializing) : base(deserializing) { }
private SuccessfulOffspringAnalyzer(SuccessfulOffspringAnalyzer original, Cloner cloner) : base(original, cloner) { }
public SuccessfulOffspringAnalyzer()
: base() {
Parameters.Add(new ValueParameter("SuccessfulOffspringFlag", "The name of the flag which indicates if the individual was successful.", new StringValue("SuccessfulOffspring")));
Parameters.Add(new ValueParameter>("CollectedValues", "The properties of the successful offspring that should be collected.", new ItemCollection()));
Parameters.Add(new ValueLookupParameter("Results", "The result collection where the succedd progress analysis results should be stored."));
Parameters.Add(new LookupParameter("Generations", "The current number of generations."));
Parameters.Add(new ValueParameter("Depth", "The depth of the individuals in the scope tree.", new IntValue(1)));
}
public override IOperation Apply() {
ResultCollection results = ResultsParameter.ActualValue;
List scopes = new List() { ExecutionContext.Scope };
for (int i = 0; i < DepthParameter.Value.Value; i++)
scopes = scopes.Select(x => (IEnumerable)x.SubScopes).Aggregate((a, b) => a.Concat(b)).ToList();
ItemCollection collectedValues = CollectedValues.Value;
foreach (StringValue collected in collectedValues) {
//collect the values of the successful offspring
Dictionary counts = new Dictionary();
for (int i = 0; i < scopes.Count; i++) {
IScope child = scopes[i];
string successfulOffspringFlag = SuccessfulOffspringFlag.Value.Value;
if (child.Variables.ContainsKey(collected.Value) &&
child.Variables.ContainsKey(successfulOffspringFlag) &&
(child.Variables[successfulOffspringFlag].Value is BoolValue) &&
(child.Variables[successfulOffspringFlag].Value as BoolValue).Value) {
String key = child.Variables[collected.Value].Value.ToString();
if (!counts.ContainsKey(key))
counts.Add(key, 1);
else
counts[key]++;
}
}
//create a data table containing the collected values
DataTable successProgressAnalysis;
string resultKey = "Success Progress " + collected.Value;
if (!results.ContainsKey(resultKey)) {
successProgressAnalysis = new DataTable();
successProgressAnalysis.Name = "Success Progress Analysis";
results.Add(new Result(resultKey, successProgressAnalysis));
} else {
successProgressAnalysis = results[resultKey].Value as DataTable;
}
int successfulCount = 0;
foreach (string key in counts.Keys) {
successfulCount += counts[key];
}
foreach(String value in counts.Keys) {
DataRow row;
if (!successProgressAnalysis.Rows.ContainsKey(value)) {
row = new DataRow(value);
int iterations = GenerationsParameter.ActualValue.Value;
//fill up all values seen the first time
for (int i = 1; i < iterations; i++)
row.Values.Add(0);
successProgressAnalysis.Rows.Add(row);
} else {
row = successProgressAnalysis.Rows[value];
}
row.Values.Add(counts[value] / (double)successfulCount);
}
//fill up all values that are not present in the current generation
foreach (DataRow row in successProgressAnalysis.Rows) {
if (!counts.ContainsKey(row.Name))
row.Values.Add(0);
}
}
return base.Apply();
}
}
}